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Python courses

949 Courses

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California Institute of Technology Universidad de los Andes

Visualización de Datos - Gestión Empresarial

Visualización de Datos - Gestión Empresarial La visualización de datos surge como una poderosa herramienta que transforma los datos sin procesar en representaciones significativas y visualmente convincentes. Mejora la comunicación y la colaboración dentro de las organizaciones, facilitando el intercambio de conocimientos y hallazgos entre.
provider Coursera
sessions On-Demand
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California Institute of Technology University of Naples Federico II

Applied Python Data Engineering

Applied Python Data Engineering Learn how to use data engineering to leverage big data for business strategy, data analysis, or machine learning and AI. By completing this course series, you'll empower yourself with the knowledge and proficiency required to build efficient data pipelines, manage cutting-edge platforms like Hadoop, Spar.
provider Coursera  Specialization
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California Institute of Technology

How Neural Networks Learn: Exploring Architecture, Gradient Descent, and Backpropagation

How Neural Networks Learn: Exploring Architecture, Gradient Descent, and Backpropagation Neural networks drive many artificial intelligence applications today. This course will teach you what’s behind the magic—the dynamics of training neural networks, including backpropagation, gradient descent, and how to optimize network performance. So, you.
California Institute of Technology Swayam

Teaching & Learning (TL) Practices for Python Programming

Teaching & Learning (TL) Practices for Python Programming Teaching and Learning practices of Python programming for the faculty members is paramount in today's educational landscape due to its presence in all Engineering and Technology curriculum and its multifaceted benefits. Its versatility spans numerous domains, from web development to data s.
provider Swayam
sessions 28th Jan, 2024
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California Institute of Technology Coursera

Building Production-Ready Apps with Large Language Models

Building Production-Ready Apps with Large Language Models In the age of artificial intelligence (AI), it is essential to learn how to apply the power of large language models (LLMs) for building various production-ready applications. In this hands-on course, learners will gain the necessary skills for building and responsibly deploying a conversa.
provider Coursera
sessions On-Demand
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California Institute of Technology FutureLearn

Recommender Systems in Python

Recommender Systems in Python Build a Recommender System with National Tsing Hua University If you’ve ever watched a recommended film on Netflix or listened to a suggested playlist on Spotify, you have used a recommender system. On this six-week course from National Tsing Hua University, you’ll learn why so many platforms incorporate recomme.
provider FutureLearn
sessions On-Demand
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California Institute of Technology

Introduction to Python for AI Programmers

Introduction to Python for AI Programmers Start coding with Python and harness the power of its extensive libraries and automation scripts to solve complex problems efficiently. Categories: Artificial Intelligence Courses, Python Courses, Object-oriented programming Courses
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California Institute of Technology Udacity

Introduction to Neural Networks with TensorFlow

Introduction to Neural Networks with TensorFlow | Udacity Master the basics of neural networks using Python and TensorFlow, and apply your knowledge to build a functional image classifier. This course guides you through training a deep learning model on an image dataset and deploying it to classify new images. University: Udacity Categories: Pyt.
provider Udacity
sessions On-Demand
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California Institute of Technology Udacity

Introduction to Neural Networks with PyTorch

Learn the fundamentals of neural networks with Python and PyTorch, and then use your new skills to create your own image classifier—an application that will first train a deep learning model on a dataset of images and then use the trained model to classify new images. University: Udacity Provider: Udacity Python Courses Computer Vision.
provider Udacity
sessions On-Demand
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California Institute of Technology Arizona State University

Data Mining for Smart Cities

Data Mining for Smart Cities | Arizona State University | Coursera Internet of things (IoT) has become a significant component of urban life, giving rise to “smart cities.” These smart cities aim to transform present-day urban conglomerates into citizen-friendly and environmentally sustainable living spaces. The digital infrastructure of smart c.
provider Coursera
sessions On-Demand

Your speed of mastering the profession and success in this matter largely depends on which programming language you start learning first. How to choose it? Let's answer using a python ai course as an example.

What criteria should you use to choose your first language?

For learning to progress quickly, the programming language must have a simple syntax. It is desirable that it be high-level and flexible - then you can experiment with different options for solving the same problem.

Of course, it cannot be said that the choice of the first language always determines how successful the student’s future career path will be. But it can have a powerful impact on professional development as well as self-learning skills.

Even if we talk about spoken languages, you’ve probably heard the statement that the language a person speaks determines his thinking: “the number of languages you know, the number of times you are human.” This statement is also relevant for programming. Note that this skill is often described as an effective tool for developing thinking that teaches people to solve problems well.

When choosing the first language, the following criteria are also taken into account:

It’s difficult to name an ideal programming language to learn as a first language, but Python definitely meets most of the listed criteria, which means it can be safely recommended to beginners.

Scope of Python

Scripting languages are rapidly gaining popularity these days. They are already used to write software even more often than traditional system ones. Python is compatible with all major operating systems and platforms. You will learn this information at a python course. It is actively used in science, web development, Machine Learning, game creation, complex visual effects, and more.

Community, technical documentation

The Python language has gathered a large community of developers from all over the world who are engaged not only in its study, but also in its development. The documentation base related to Python is extensive and well-developed, so even a beginner will not have much difficulty finding answers to almost all questions that arise. He also has enough standard libraries for all occasions, and there are even more open-source repositories.

Simplicity

Because Python has a simple syntax, its code is easy to read and understand. Statements are terminated by the end of the line, and the block structure is determined by indentation.

Among the features of Python, it is worth highlighting the use of indentations that delimit blocks of code. Correct formatting is ensured by the interpreter, which prevents the creation of unreadable code. So if in other programming languages indentation is a “handwriting” and an art, then in Python it is one of the components of the syntax.

Python Strengths and Weaknesses

We have already noted above some of the advantages of a python certification course, now we propose to compare them with the disadvantages in order to objectively evaluate the language as the first one to learn.

Pluses

  1. Easy to learn.

  2. Laconic.

  3. Easy and understandable syntax.

  4. Interpretability.

  5. Wide scope of use.

  6. Demand.

  7. Dynamic typing.

  8. A large number of libraries.

  9. Lots of technical documentation and training materials.

  10. Cross-platform.

Minuses

  1. Slow program execution speed: Because dynamically typed languages execute code line by line, this makes it difficult to develop software that requires high performance. However, the programmer's productivity increases, which can be considered a kind of compensation.

  2. Programs written in Python require a lot of memory.

  3. Because there is no check during compilation, errors sometimes occur when executing the code. Because of this, very high-quality testing is required before production launch.

Conclusion

Python is a clear, easy-to-learn, universal, in-demand and promising language. Despite the presence of certain disadvantages, its advantages significantly outweigh all the disadvantages, especially when it comes to novice programmers. That's why a python online course from AI Eeducation is a great choice to start your IT career!